Gong Haiyan, Ma Fuqiang, Zhang Xiaotong
Institute for Advanced Materials and Technology, University of Science and Technology Beijing, Beijing 100083, P. R. China.
School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, P. R. China.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2023 Oct 25;40(5):1033-1039. doi: 10.7507/1001-5515.202303046.
Chromatin three-dimensional genome structure plays a key role in cell function and gene regulation. Single-cell Hi-C techniques can capture genomic structure information at the cellular level, which provides an opportunity to study changes in genomic structure between different cell types. Recently, some excellent computational methods have been developed for single-cell Hi-C data analysis. In this paper, the available methods for single-cell Hi-C data analysis were first reviewed, including preprocessing of single-cell Hi-C data, multi-scale structure recognition based on single-cell Hi-C data, bulk-like Hi-C contact matrix generation based on single-cell Hi-C data sets, pseudo-time series analysis, and cell classification. Then the application of single-cell Hi-C data in cell differentiation and structural variation was described. Finally, the future development direction of single-cell Hi-C data analysis was also prospected.
染色质三维基因组结构在细胞功能和基因调控中起关键作用。单细胞Hi-C技术能够在细胞水平捕获基因组结构信息，这为研究不同细胞类型之间基因组结构的变化提供了契机。最近，已经开发出了一些用于单细胞Hi-C数据分析的优秀计算方法。本文首先综述了单细胞Hi-C数据分析的现有方法，包括单细胞Hi-C数据的预处理、基于单细胞Hi-C数据的多尺度结构识别、基于单细胞Hi-C数据集生成类似批量Hi-C的接触矩阵、伪时间序列分析和细胞分类。然后描述了单细胞Hi-C数据在细胞分化和结构变异中的应用。最后，还展望了单细胞Hi-C数据分析的未来发展方向。
